Improving the prevention and detection of preinvasive ductal carcinoma in situ (DCIS) is expected to lower both morbidity and mortality from breast cancer. Transgenic mouse models can be used as a ‘test bed’ to develop new imaging methods and to evaluate the efficacy of candidate preventive therapies. We hypothesized that despite its microscopic size, early murine mammary cancer, including DCIS, might be accurately detected by MRI. C3(1) SV40 TAg female mice (n = 23) between 10 and 18 weeks of age were selected for study. Eleven mice were subjected to in vitro imaging using a T2-weighted spin echo sequence and 12 mice were selected for in vivo imaging using a T1-weighted gradient echo, a T2-weighted spin echo and high spectral and spatial resolution imaging sequences. The imaged glands were carefully dissected, formalin fixed and paraffin embedded, and then H&E stained sections were obtained. The ratio of image-detected versus histologically detected cancers was obtained by reviewing the MR images and H&E sections independently and using histology as the gold standard. MR images were able to detect 12/12 intramammary lymph nodes, 1/1 relatively large (~5 mm) tumor, 17/18 small (~1 mm) tumors and 13/16 ducts distended with DCIS greater than 300 μm. Significantly, there were no false positives—i.e., image detection always corresponded to a histologically detectable cancer in this model. These results indicate that MR imaging can reliably detect both preinvasive in situ and early invasive mammary cancers in mice with high sensitivity. This technology is an important step toward the more effective use of non-invasive imaging in pre-clinical studies of breast cancer prevention, detection and treatment.

Pharmacokinetic modeling is a promising quantitative analysis technique for cancer diagnosis. However, diagnostic dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) of the breast is commonly performed with low temporal resolution. This limits its clinical utility. We investigated for a range of temporal resolutions whether pharmacokinetic parameter estimation is impacted by the use of data-derived arterial input functions (AIFs), obtained via analysis of dynamic data from a reference tissue, as opposed to the use of a standard AIF, often obtained from the literature. We hypothesized that the first method allows the use of data at lower temporal resolutions than the second method. Test data were obtained by downsampling high-temporal-resolution rodent data via a k-space-based strategy. To fit the basic Tofts model, either the data-derived or the standard AIF was used. The resulting estimates of K(trans) and v(e) were compared with the standard estimates obtained by using the original data. The deviations in K(trans) and v(e), introduced when lowering temporal resolution, were more modest using data-derived AIFs compared with using a standard AIF. Specifically, lowering the resolution from 5 to 60 s, the respective changes in K(trans) were 2% (non-significant) and 18% (significant). Extracting the AIF from a reference tissue enables accurate pharmacokinetic parameter estimation for low-temporal-resolution data.

#6011 Background: Understanding the natural history of breast cancer is important for effective patient management and treatment. For example, some evidence suggests that preinvasive ductal carcinoma in situ (DCIS) may be over-treated, since not all will progress to invasive cancer. Unfortunately, due to obligate surgical excision of newly diagnosed breast cancers, the natural history of disease is difficult to study in women. However, mouse models of breast cancer can serve as an alternative; the purpose of this study was to use magnetic resonance imaging (MRI) to investigate the progression of DCIS into invasive cancer in a transgenic model.
 Methods:12 SV40 Tag mice were imaged every 2-3 weeks (wks) starting at 10 wks of age. SV40 mice develop mammary cancer similar to DCIS and IDC, and usually live to 22 wks when they succumb to breast cancer. T1-weighted gradient echo images of inguinal mammary glands were obtained. DCIS lesions and invasive tumors were identified and volumes were measured over time. For each lesion we measured: the time at initial development (TDCIS and Ttumor), the growth rate of DCIS and invasive tumors (calculated from 'V=V0exp(αt)'), and for DCIS lesions that progressed to invasive tumors the progression time Tprog was measured.
 Results:DCIS (n=21) and invasive (n=16) tumors developed, at an average initial age of TDCIS =12.7±2.6 wks and Ttumor =16.3±3.1 wks, and at an initial volume of 0.3±0.2 mm3 and 1.7 mm3, respectively. The average growth rate for DCIS lesions was αDCIS= 0.08±0.23 wk-1, significantly smaller than that of invasive tumors (αtumor= 0.55±0.35 wk-1, p =0.001). 9/21 DCIS lesions progressed to invasive cancers in an average time of Tprog=4.56 ± 1.9 wks(Figure 1a). 11/21 DCIS did not progress within the study window and 5/21 were stable for over 8 wks (Figure 1b).
 
 The volume of DCIS was not a predictor of progression, but there was a trend for DCIS growth rate to be related to eventual development of invasiveness.
 Discussion:To our knowledge, the results reported here are the first direct measurements of the timescales and characteristics of progression from in situ to invasive carcinoma. Surprisingly, even in transgenic mice that are strongly pre-disposed to develop cancer, some DCIS lesions did not progress to invasive cancer. Interestingly, DCIS volume did not predict future progression to invasive tumors, but growth rate may have been a predictor. The methods and data here provide a foundation for using MRI in pre-clinical studies of early cancer progression, prevention and targeted treatment. Extensions of this pilot study may yield image-based biomarkers of progressing vs. indolent DCIS. Citation Information: Cancer Res 2009;69(2 Suppl):Abstract nr 6011.

Purpose: An improved understanding of T2* in normal breast and intraductal cancer could lead to improvements in diagnostic accuracy. This study characterizes T2* in both a preclinical model of breast/mammary cancer (SV40Tag) and in healthy (FVB/N) mice. At ∼12 weeks, C3(1)SV40Tag mice develop mammary in situ neoplasms (MIN) that resemble ductal carcinoma in situ (DCIS) in women. Method and Materials: Eight SV40Tag and six FVB/N mice were imaged using a 9.4T Bruker magnet. Respiratory gated multi‐gradient echo pulse sequences were used to measure T2* with equivalent TR ∼1000ms, minimum TE of 1.5ms, 9 echoes at 3ms spacing. Generally, T2* was calculated by fitting the MRI signal intensity to a single exponential decay function. However, when fat was present, a modulus of complex double exponential decay function was needed. Results: For SV40Tag mice, T2* of muscle, lymph node, and tumor can be calculated from a single exponential function. T2* of normal mammary gland (NMG) and MIN need to be extracted from the modulus of complex function due to the fatty signal. Conversely, for FVB/N mice, all T2* can be calculated from single exponential function. On average muscle, tumor and NMG water components have slightlysmaller T2* values (∼15ms), but lymph node and NMG water components have slightly smaller T2* values (∼9.5ms). The fat in NMG and MIN have the smallest T2* values (∼3.8ms). In addition, NMG in SV40Tag is fattier than in FVB/N mice (57% vs. 12%, p<0.0001) for the selected ROIs. Conclusion: To accurately determine T2*, it is necessary to separate water/fat in fat‐rich mammary glands. In this pilot study, MIN lesions exhibit a larger separation between the long and short T2* values in comparison to NMG. Additionally, SV40Tag mice exhibit a higher percentage fat in NMG ROIs due to genetic differences.

#4025 Background: Dynamic contrast enhanced magnetic resonance imaging (DCEMRI) has demonstrated superior sensitivity for detecting earlier cancers compared with x-ray mammography, and is being used increasingly for high-risk screening, diagnostic imaging and to evaluate extent of malignant disease. When assessing lesion malignancy both the morphology and contrast uptake and washout—or kinetics—of the lesion are important. At our institution DCEMRI breast examinations have been performed on three different MR systems. The purpose of this study was to compare the MR kinetic curve data of malignant lesions acquired by these systems.&#x2028; Methods: 445 patients with 485 malignant lesions were selected for an IRB approved review. The lesions were classified as ductal carcinoma in situ (DCIS), invasive ductal carcinoma (IDC) and 'other'. Dynamic MR protocol: 1 pre and 3-7 post-contrast images, acquired on a system using a non fat-suppressed dynamic sequence (NFS) and 2 newer systems by different manufacturers using fat suppressed dynamic sequences (FS1 and FS2). Kinetic curve data was processed and displayed on a CADstream workstation. Analysis of kinetic curve shape was made by an experienced radiologist according to the BI-RADS lexicon. Several quantitative kinetic parameters were calculated, both directly from the curve data and after fitting to an empirical mathematical model (EMM). The kinetic parameters of malignant lesions were compared between the three systems.&#x2028; Results: 299 malignant lesions (185 IDC, 57 DCIS) were imaged on NFS, 104 lesions (69 IDC, 21 DCIS) on FS1, and 82 on FS2 (61 IDC, 17 DCIS). Compared to both systems NFS and FS1, IDC lesions acquired on FS2 demonstrated significantly lower initial enhancement, longer time to peak enhancement and slower washout rate (p &lt; 0.0004). 80% of IDC lesions acquired on FS1 were classified as 'washout', compared with only 46% of IDC lesions on FS2. On both FS1 and FS2, we did not find a difference in the kinetic parameters of IDC vs. DCIS lesions. However, IDC lesions imaged on NFS exhibited significantly higher contrast uptake, shorter time to peak and stronger washout compared to DCIS lesions (p &lt; 0.0001).&#x2028; Discussion: The kinetic curve data of malignant lesions acquired by one system exhibited significantly lower initial contrast uptake and different curve shape compared with the other two. In addition, on both newer systems, the kinetic parameters of DCIS were comparable with IDC, which is contrary to what was found on the older system. Differences in k-space sampling, T1 weighting or magnetization transfer effects may be possible explanations. The results of this study underscore the importance of developing standardized acquisition and analysis methods, to ensure that across all available systems (i) malignant lesions are sufficiently conspicuous and thus reliably detected and (ii) interpretation of kinetic data is consistent. Citation Information: Cancer Res 2009;69(2 Suppl):Abstract nr 4025.